class_docstr: This class represents the internal state of individual tracked objects observed as bbox.
  
  Args:
      bbox (np.array): bbox in [x1,y1,x2,y2,score] format.
      delta_t (int): delta_t of previous observation
class_docstr_tok: ["This","class","represents","the","internal","state","of","individual","tracked","objects","observed","as","bbox",".","Args",":","bbox","(","np.array",")",":","bbox","in","[","x1",",","y1",",","x2",",","y2",",","score","]","format",".","delta_t","(","int",")",":","delta_t","of","previous","observation"]
code: def get_state(self):
      return convert_x_to_bbox(self.kf.x, score=self.score)
  
file_path: PaddleDetection/ppdet/modeling/mot/tracker/ocsort_tracker.py
imports: import numpy
  from ..matching.ocsort_matching import associate, linear_assignment, iou_batch, associate_only_iou
  from ..motion.ocsort_kalman_filter import OCSORTKalmanFilter
  from ppdet.core.workspace import register, serializable
label_desc: Use image node_id 4 for calling the KalmanBoxTracker obj's underlying member method code with example usage: obj.get_state() and returns: convert_x_to_bbox